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Adam Finkel-Gates – Journal of Learning Development in Higher Education, 2025
This study examines the impact of AI, particularly ChatGPT, on academic integrity and assessment practices in higher education. As AI integration grows, concerns about its potential to undermine academic rigour and increase inequalities have surfaced. Through interviews with students and a lecturer, the research explores the benefits and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation Methods
Olaperi Okuboyejo; Sigrid Ewert; Ian Sanders – ACM Transactions on Computing Education, 2025
Regular expressions (REs) are often taught to undergraduate computer science majors in the Formal Languages and Automata (FLA) course; they are widely used to implement different software functionalities such as search mechanisms and data validation in diverse fields. Despite their importance, the difficulty of REs has been asserted many times in…
Descriptors: Automation, Feedback (Response), Error Patterns, Error Correction
Yusuf Oc; Chahna Gonsalves; La Toya Quamina – Journal of Marketing Education, 2025
The integration of generative artificial intelligence (AI) tools is a paradigm shift in enhanced learning methodologies and assessment techniques. This study explores the adoption of generative AI tools in higher education assessments by examining the perceptions of 353 students through a survey and 17 in-depth interviews. Anchored in the Unified…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Zi Yang; Junjie Gavin Wu; Haoran Xie – Asia Pacific Journal of Education, 2025
The emergence of generative artificial intelligence (GAI) in the past two years is exerting profound effects throughout society. However, while this new technology undoubtedly promises substantial benefits, its disruptive nature also means that it poses a variety of challenges. The field of education is no exception. This position paper intends to…
Descriptors: Artificial Intelligence, Ethics, Technology Uses in Education, Natural Language Processing
Christopher Mah; Mei Tan; Lena Phalen; Alexa Sparks; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2025
Effective writing feedback is a powerful tool for enhancing student learning, encouraging revision, and increasing motivation and agency. Yet, teachers face many challenges that prevent them from consistently providing effective writing feedback. Recent advances in generative artificial intelligence (AI) have led educators and researchers to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Writing Evaluation
Sedat Yigit; Soner Berse; Ezgi Dirgar; Seçil Gülhan Güner – Innovations in Education and Teaching International, 2025
Artificial Intelligence (AI) has significantly impacted the field of education, particularly in health sciences, where tools such as ChatGPT are increasingly utilised. ChatGPT, powered by AI, presents both opportunities and challenges that warrant investigation. This qualitative study explored the perceptions, experiences, and expectations of…
Descriptors: Undergraduate Students, Student Attitudes, Allied Health Occupations Education, Artificial Intelligence
Deliang Wang; Gaowei Chen – British Journal of Educational Technology, 2025
Classroom dialogue is crucial for effective teaching and learning, prompting many professional development (PD) programs to focus on dialogic pedagogy. Traditionally, these programs rely on manual analysis of classroom practices, which limits timely feedback to teachers. To address this, artificial intelligence (AI) has been employed for rapid…
Descriptors: Classroom Communication, Artificial Intelligence, Technology Uses in Education, Models
Shilpi Taneja; Siddhartha Sankar Biswas; Bhavya Alankar; Harleen Kaur – Electronic Journal of e-Learning, 2025
This paper presents the design of a personalized learning agent powered by the Agentic RAG technique. The agent can interpret learners' queries and autonomously decide which tools should be used to generate the most suitable response. When the learner shares an Open Educational Resource (OER) they wish to learn from, the agent first breaks the…
Descriptors: Artificial Intelligence, Natural Language Processing, Open Educational Resources, Individualized Instruction
Nihal Dulkadir Yaman – European Journal of Education, 2025
Artificial intelligence (AI) is a technology that has been used quite effectively in the 21st century and has the potential to directly affect education as well as many other fields. AI is supported in many areas such as developing skills in education, increasing the effectiveness of education and student motivation, contributing to the…
Descriptors: Preservice Teachers, Teacher Developed Materials, Artificial Intelligence, Natural Language Processing
Southby, Lucy; Harding, Sam; Phillips, Veronica; Wren, Yvonne; Joinson, Carol – International Journal of Language & Communication Disorders, 2021
Background: Speech development requires intact and adequately functioning oral anatomy and cognitive 'speech processing' skills. There is evidence that speech input processing skills are associated with speech output problems in children not born with a cleft. Children born with cleft palate ± lip (CP±L) are at high risk of developing disordered…
Descriptors: Congenital Impairments, Language Processing, Speech Impairments, Children
Luthra, Sahil; Magnuson, James S.; Myers, Emily B. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2021
A challenge for listeners is to learn the appropriate mapping between acoustics and phonetic categories for an individual talker. Lexically guided perceptual learning (LGPL) studies have shown that listeners can leverage lexical knowledge to guide this process. For instance, listeners learn to interpret ambiguous /s/-/[esh]/ blends as /s/ if they…
Descriptors: Listening, Language Processing, Ambiguity (Context), Phonemes
Zhao, Licui; Kojima, Haruyuki; Yasunaga, Daichi; Irie, Koji – Journal of Psycholinguistic Research, 2023
In order to examine whether syntactic processing is a necessary prerequisite for semantic integration in Japanese, cortical activation was monitored while participants engaged in silent reading task. Congruous sentences (CON), semantic violation sentences (V-SEM), and syntactic violation sentences (V-SYN) were presented in the experiment. The…
Descriptors: Japanese, Syntax, Semantics, Brain Hemisphere Functions
Pan, Jinger; Wang, Aiping; McBride, Catherine; Cho, Jeung-Ryeul; Yan, Ming – Scientific Studies of Reading, 2023
Purpose: The present study tested parafoveal morphological processing during sentence reading with two eye-tracking experiments, making use of an implicit measurement of morphological awareness. In Chinese and Korean, each character form typically corresponds to multiple mental lexicons, leading to morphological ambiguity. Method: Using the…
Descriptors: Morphology (Languages), Language Processing, Sentences, Eye Movements
Quoc, Nguyen Long; Van, Le Ha – Cogent Education, 2023
Vocabulary plays a significant role in the learning process of English as a Foreign Language (EFL) students, especially undergraduates who need to read academic materials and listen to specialized lectures in English. However, retaining lexical items is still a challenging task for many EFL learners. The current study seeks to examine the…
Descriptors: Foreign Countries, Second Language Learning, English (Second Language), Constructivism (Learning)
Kalaitzi, Christina; Panos, Spiros – International Journal of Early Years Education, 2023
This paper aims to investigate to what extent preschoolers' narrative speech can be affected by the combined use of five narrative elements: narrative framing, narrative basic structure, intertextual hero, plot subversion and image-text interaction. It presents an intervention aiming to teach these elements to an experimental group of…
Descriptors: Speech Communication, Comparative Analysis, Preschool Children, Narration

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